Hacia un modelo explicativo del rendimiento académico: variables orécticas y cognitivas
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Palabras clave

academic performance
creativity
reasoning
motivation
personality rendimiento académico
creatividad
razonamiento
motivación
personalidad

Cómo citar

González-Primo, F., Montes-Álvarez, P., Postigo, Álvaro, Menéndez-Aller, Álvaro, & García-Cueto, E. (2022). Hacia un modelo explicativo del rendimiento académico: variables orécticas y cognitivas. R.E.M.A. Revista electrónica De metodología Aplicada, 24(2), 45–59. https://doi.org/10.17811/rema.24.2.2022.45-59

Resumen

Introducción: Razonamiento, creatividad, apertura, motivación, responsabilidad y neuroticismo son variables que habitualmente se han asociado con el rendimiento académico, sin embargo, apenas existen estudios que examinen conjuntamente los efectos de estos factores. El objetivo fue estudiar algunas de las variables que afectan al rendimiento académico y construir un modelo que las incluya. Método: 281 estudiantes universitarios (M = 21.16; DT = 3.14; 20% hombres) a los que se aplicaron el NEO-FFI, el Factor R del PMA, un test de creatividad y una escala de Motivación de Logro de forma presencial. Resultados: Los instrumentos utilizados obtuvieron unas buenas propiedades psicométricas. Se encontraron diferencias estadísticamente significativas en creatividad en función del sexo y en creatividad y razonamiento en función del tipo de estudios. Se propuso un modelo mediante ecuaciones estructurales para explicar el rendimiento académico. Conclusiones: El rendimiento académico puede explicarse a partir de varias variables: razonamiento, creatividad, apertura, motivación y responsabilidad.

https://doi.org/10.17811/rema.24.2.2022.45-59
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Citas

Andreas, S. F. K., Zech, S., Coyle, T. R., y Rindermann, H. (2016). Unconventionality and originality: Does self-assessed unconventionality increase original achievement? Creativity Research Journal, 28(2), 198–206. https://doi.org/10.1080/10400419.2016.1162556

Aranguren, M. (2015). Influencia del conocimiento previo sobre el Test de Pensamiento Creativo de Torrance. International Journal of Psychological Research, 8(2), 75–89. https://doi.org/10.21500/20112084.1511

Baer, J., y Kaufman, J. C. (2008). Gender differences in creativity. The Journal of Creative Behavior, 42(2), 75–105. https://doi.org/10.1002/j.2162-6057.2008.tb01289.x

Batey, M., y Furnham, A. (2006). Creativity, intelligence, and personality: A critical review of the scattered literature. Genetic, Social, and General Psychology Monographs, 132(4), 355–429. https://doi.org/10.3200/MONO.132.4.355-430

Beaty, R. E., Silvia, P. J., Nusbaum, E. C., Jauk, E., y Benedek, M. (2014). The roles of associative and executive processes in creative cognition. Memory & Cognition, 42(7), 1186–1197. https://doi.org/10.3758/s13421-014-0428-8

Cáceres, S. F. (2017). Relación entre los factores de personalidad y depresión con el rendimiento académico en estudiantes de una facultad en una universidad privada de Lima Metropolitana (Tesis doctoral). Universidad peruana Cayetano Heredia, Lima.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2ªed.). Erlbaum.

Cordero, A., Seisdedos, N., González, M., y de la Cruz, M. V. (2007). PMA: Aptitudes Mentales Primarias (manual técnico) [PMA: Primary Mental Abilities. (Technical manual)]. TEA Ediciones.

Costa, P. T., y McCrae, R. R. (2002). NEO PI-R Inventario De Personalidad NEO Revisado Manual. TEA Ediciones.

Crawford, I., y Wang, Z. (2015). The impact of individual factors on the academic attainment of Chinese and UK students in higher education. Studies in Higher Education, 40(5), 902–920. https://doi.org/10.1080/03075079.2013.851182

Crew Universidades Españolas (2018). La Universidad española en cifras. http://www.crue.org/SitePages/La-Universidad-Española-en-Cifras.aspx

Cuesta, M., Suárez-Álvarez, J., Lozano, L. M., García-Cueto, E., & Muñiz, J. (2018). Assessment of eight entrepreneurial personality dimensions: Validity evidence of the BEPE battery. Frontiers in Psychology, 9, 2352, 1-10. https://doi.org/10.3389/fpsyg.2018.02352

De Sixte, R., Jáñez, A., Ramos, M., y Rosales, J. (2020). Motivación, rendimiento en matemáticas y prácticas familiares: Un estudio de su relación en 1º de Educación Primaria. Psicología Educativa, 26, 67–75. https://doi.org/10.5093/psed2019a16

Di Domenico, S. I., y Fournier, M. A. (2015). Able, ready, and willing: Examining the additive and interactive effects of intelligence, conscientiousness, and autonomous motivation on undergraduate academic performance. Learning and Individual Differences, 40, 156–162. https://doi.org/10.1016/j.lindif.2015.03.016

Ding, L., Wei, X., y Liu, X. (2016). Variations in university students’ scientific reasoning skills across majors, years, and types of institutions. Research in Science Education, 46(5), 613–632. https://doi.org/10.1007/s11165-015-9473-y

Echavarri, M., Godoy, J., y Olaz, F. (2007). Diferencias de género en habilidades cognitivas y rendimiento académico en estudiantes universitarios. Universitas Psychologica, 6(2), 319–329.

Etikan, I. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11

Evers, A., Muñiz, J., Hagemeister, C., Høstmælingen, A., Lindley, P., Sjöberg, A., y Bartram, D. (2013). Assessing the quality of tests: Revision of the EFPA review model. Psicothema, 29(3), 236–240. https://doi.org/10.7334/psicothema2013.97

Fenollar, P., Román, S., y Cuestas, P. (2007). University students’ academic performance: An integrative conceptual framework and empirical analysis. British Journal of Educational Psychology, 77(4), 873–891. https://doi.org/10.1348/000709907X189118

Fuller, B., y Marler, L. E. (2009). Change driven by nature: A meta-analytic review of the proactive personality literature. Journal of Vocational Behavior, 75(3), 329–345. https://doi.org/10.1016/j.jvb.2009.05.008

Furnham, A., Nuygards, S., y Chamorro-Premuzic, T. (2013). Personality, assessment methods and academic performance. Instructional Science, 41(5), 975–987. https://doi.org/10.1007/s11251-012-9259-9

Gajda, A., Karwowski, M., y Beghetto, R. A. (2017). Creativity and academic achievement: A meta-analysis. Journal of Educational Psychology, 109(2), 269–299. https://doi.org/10.1037/edu0000133

García-Cueto, E. (1984). Estructura factorial de la fluidez verbal escrita en sujetos de 11 a 18 años (Tesis doctoral). Universidad Complutense, Madrid.

Gatica, A., y Bizama, M. (2019). Inteligencia fluida y creatividad: Un estudio en escolares de 6 a 8 años de edad. Pensamiento Psicológico, 17(1), 113–120. https://doi.org/10.11144/Javerianacali.PPSI17-1.ifce.

Glück, J., Ernst, R., y Unger, F. (2002). How creatives define creativity: Definitions reflect different types of creativity. Creativity Research Journal, 14(1), 55–67. https://doi.org/10.1207/S15326934CRJ1401_5

Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement Routledge.

He, W.J. (2018). A 4-year longitudinal study of the sex-creativity relationship in childhood, adolescence, and emerging adulthood: Findings of mean and variability analyses. Frontiers in Psychology, 9, 2331. https://doi.org/10.3389/fpsyg.2018.02331.

Hu, L., y Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55. https://doi.org/10.1080/10705519909540118

Janošević, M., y Petrović, B. (2018). Effects of personality traits and social status on academic achievement: Gender differences. Psychology in the Schools, 56(4), 497–509. https://doi.org/10.1002/pits.22215

Kaufman, J. C., Baer, J., y Gentile, C. A. (2004). Differences in gender and ethnicity as measured by ratings of three writing tasks. The Journal of Creative Behavior, 38(1), 56–69. https://doi.org/10.1002/j.2162-6057.2004.tb01231.x

Khan, R. M. S., Nawaz, K., Yaseen, S., Rouf, A., Maryam, M., y Tabassum, S. (2018). Relationship between birth order, personality and academic performance. Rawal Medical Journal, 43(1), 39–44.

Kim, J., y Michael, W. B. (1995). The relationship of creativity measures to school achievement and to preferred learning and thinking style in a sample of Korean high school students. Educational and Psychological Measurement, 55(1), 60–74. https://doi.org/10.1177/0013164495055001006

Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.

Komarraju, M., Karau, S. J., y Schmeck, R. R. (2009). Role of the Big Five personality traits in predicting college students’ academic motivation and achievement. Learning and Individual Differences, 19(1), 47–52. https://doi.org/10.1016/j.lindif.2008.07.001

Lorenzo-Seva, U., y Ferrando, P.J. (2006). FACTOR: A computer program to fit the exploratory factor analysis model. Behavioral Research Methods, Instruments and Computers, 38, 88–91.

Mammadov, S., Cross, T. L., y Ward, T. J. (2018). The Big Five personality predictors of academic achievement in gifted students: Mediation by self-regulatory efficacy and academic motivation. High Ability Studies, 29(2), 111–133. https://doi.org/10.1080/13598139.2018.1489222

McCrae, R. R., y Costa P. T. (1987). Validation of the Five Factor Model of Personality across instruments and observers. Journal of Personality and Social Psychology, 52(1), 81-90. https://doi.org/1037/0022-3514.52.1.81

Mendoza-Recarte, L. (2017). Baremos del test de aptitudes mentales primarias para universitarios hondureños. Revista Ciencia Y Tecnología, 19, 198–227. https://doi.org/10.5377/rct.v0i19.4281

Mourgues, C., Tan, M., Hein, S., Elliott, J. G., y Grigorenko, E. L. (2016). Using creativity to predict future academic performance: An application of Aurora’s five subtests for creativity. Learning and Individual Differences, 51, 378–386. https://doi.org/10.1016/j.lindif.2016.02.001

Muñiz, J., Suárez-Alvárez, J., Pedrosa, I., Fonseca-Pedrero, E., y García-Cueto, E. (2014). Enterprising personality profile in youth: Components and assessment. Psicothema, 26(4), 545–553. https://doi.org/10.7334/psicothema2014.182

Muthén, L. K., y Muthén, B. O. (2017). Mplus user’s guide (8th ed.). Muthén y Muthén.

Nori, R., Signore, S., y Bonifacci, P. (2018). Creativity style and achievements: An investigation on the role of emotional competence, individual differences, and psychometric intelligence. Frontiers in Psychology, 9, 1826. https://doi.org/10.3389/fpsyg.2018.01826

Ohtani, K., y Hisasaka, T. (2018). Beyond intelligence: A meta-analytic review of the relationship among metacognition, intelligence, and academic performance. Metacognition and Learning, 13(2), 179–212. https://doi.org/10.1007/s11409-018-9183-8

Pedrosa, I., Juarros-Basterretxea, J., Robles-Fernández, A., Basteiro, J., y García-Cueto, E. (2014). Pruebas de bondad de ajuste en distribuciones simétricas, ¿qué estadístico utilizar? Universitas Psychologica, 14(1), 245–254. https://doi.org/10.11144/Javeriana.upsy14-1.pbad

Postigo, Á., García-Cueto, E., Cuesta, M., Menéndez-Aller, Á., Prieto-Díez, F., y Lozano, L. M. (2020). Assessment of the enterprising personality: A short form of the BEPE battery. Psicothema, 32(4), 575–582. https://doi.org/10.7334/psicothema2020.193.

Richardson, M., y Abraham, C. (2009). Conscientiousness and achievement motivation predict performance. European Journal of Personality, 23(7), 589–605. https://doi.org/10.1002/per.732

Siddiquei, N., y Khalid, D. (2018). The relationship between personality traits, learning styles and academic performance of e-learners. Open Praxis, 10(3), 249–263. https://doi.org/10.5944/openpraxis.10.3.870

Solano, L. O. (2015). Rendimiento académico de los estudiantes de secundaria obligatoria y su relación con las aptitudes mentales y las actitudes ante el estudio (Tesis doctoral). Universidad Nacional de Educación a Distancia, Madrid.

Stajkovic, A. D., Bandura, A., Locke, E. A., Lee, D., y Sergent, K. (2018). Test of three conceptual models of influence of the Big Five personality traits and self-efficacy on academic performance: A meta-analytic path-analysis. Personality and Individual Differences, 120, 238-245. https://doi.org/10.1016/j.paid.2017.08.014

Steinmayr, R., Bipp, T., y Spinath, B. (2011). Goal orientations predict academic performance beyond intelligence and personality. Learning and Individual Differences, 21(2), 196–200. https://doi.org/10.1016/J.lindif.2010.11.026

Sternberg, R. J. (1984). Toward a triarchic theory of human intelligence. Behavioral and Brain Sciences, 7(2), 269–315. https://doi.org/10.1017/s0140525x00044629

Suárez-Álvarez, J., Campillo-Álvarez, Á., Fonseca-Pedrero, E., García-Cueto, E., y Muñiz, J. (2013). Professional training in the workplace: The role of achievement motivation and locus of control. The Spanish Journal of Psychology, 16, E35. https://doi.org/10.1017/sjp.2013.19.

Suárez-Riveiro, J. M., Martínez-Vicente, M., y Valiente-Barroso, C. (2020). Rendimiento académico según distintos niveles de funcionalidad ejecutiva y de estrés infantil percibido. Psicología Educativa, 26, 77–86. https://doi.org/10.5093/psed2019a17

Thurstone, T. G. (1941). Primary mental abilities of children. Educational and Psychological Measurement, 1(1), 103–115. https://doi.org/10.1177/001316444100100110

Voyer, D., y Voyer, S. D. (2014). Gender differences in scholastic achievement: A meta-analysis. Psychological Bulletin, 140(4), 1174–1204. https://doi.org/10.1037/a0036620

Zare, M., y Flinchbaugh, C. (2018). Voice, creativity, and Big Five personality traits: A meta-analysis. Human Performance, 32(1), 30–51. https://doi.org/10.1080/08959285.2018.1550782

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